Spatial modeling of main degradation factors in the Zagros forests (Case study: Khorramabad sub-basin)

Document Type : Complete scientific research article

Authors

1 Department of Environment and Energy, Science and Research Branch, Islamic Azad University, Tehran, Iran.

2 Department of Natural Resources, Borujerd Branch, Islamic Azad University, Borujerd, Iran.

3 Prof., Research Institute of Forests and Rangelands (RIFR), Agricultural Research, Education and Extension Organization (AREEO), Tehran, Iran

Abstract

Background and Objectives: Water and soil protection, provision of living conditions for human communities and the production of by-products are the most important performances and characteristics of the Zagros forests. About a third of the country's total population lives in the Zagros region and more than 70% of the country's total nomads are found in this area; in terms of livestock, 50% of the country's livestock is located in this area. Unfortunately, today, the degradation of Zagros forests occurs for various human and ecological reasons. Due to the importance of degradation in the Zagros forests and the unfavorable conditions of this ecosystem, the present study was carried out with the aim of geographically modeling of forest degradation drivers in the Khorramabad basin.
Materials and Methods: Based on studies, five degradation drivers were identified, including overgrazing, nomadic migration routes, distribution of residences, distribution of access roads, and farming under forest canopy. For each factor, a digital map was generated and normalized by the fuzzy method in ArcGIS. The fuzzy layers were first weighted by the Analytical Hierarchical Process (AHP). Then, the conditional degradation layers were generated by the Weighted Linear Combination (WLC) method. In order to validate this layer, five classes were considered and in each class 12 sample plots of 35 × 35 m were delineated and the two factors of farming under the forest canopy and tree dieback were examined and measured. Then, based on the numerical values of the forest degradation potential layer (as a response variable) and the field surveys of five degradation drivers (as independent variables) at 30 random points, the modeling was performed by geographically weighted regression method.
Results: The results of weighting the driver factors showed that the two factors of farming under forest canopy (0.45) and overgrazing (0.29) are more important than others. Based on geographical modeling, the results of forest degradation prediction in the sample points showed that the residuals standard deviations without specific spatial pattern are distributed throughout the forest. The prediction map of continued forest degradation also showed that there is potential for degradation in all parts of the forest, however, with different intensities (-2.5 – 2.5 Std). There are three critical locations on this map that should be given special attention in the management of these forests.
Conclusion: The final results showed that in some parts of the region such as southeast, south and center, there are places that are in critical condition in terms of potential for degradation. Therefore, in order to manage the forests of the region, these locations should be given priority and in order that the degrading drivers have gained the most weight, in these sections, methods of protection and improvement of the habitat conditions must
be applied.

Keywords

References

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Journal of Wood and Forest Science and Technology
Volume 29, Issue 2
June 2022
Pages 59-75

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